在分诊工具和预警评分中加入临床虚弱量表可改善 30 天后的死亡率预测:前瞻性多中心观察研究

Jens Wretborn PhD, Samia Munir-Ehrlington MD, Erika Hörlin MSc, Daniel B. Wilhelms PhD
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引用次数: 0

摘要

目的 临床虚弱量表(CFS)可单独或与综合生命体征相结合评估虚弱程度,被认为是更好地预测急诊科(ED)老年患者死亡率的一种方法,但其对传统分诊的附加预测价值尚不明确。 方法 这是一项在瑞典三家急诊室进行的前瞻性观察研究的二次分析,采用逻辑回归法评估了CFS单独或与国家预警评分(NEWS)、分诊预警评分(TEWS)或快速急诊分诊和治疗系统(RETTS)分诊工具相结合的预后效果。主要结果为 30 天死亡率,次要结果为 7 天、90 天死亡率和入院率,以接收者操作曲线下面积 (AuROC) 分数和 95% 置信区间 (CI) 进行报告。报告了所有模型的灵敏度、特异性、准确性、预测值和似然比。 结果 共纳入1832名患者,其中分别有17人(0.9%)、57人(3.1%)和121人(6.6%)在7天、30天和90天内死亡。入院率为 43%(795/1832)。虚弱(CFS > 4)与 30 天死亡率有显著相关性(几率比 6,95% CI 3-12,p < 0.01)。所有基于 CFS 的模型对 30 天死亡率的预测结果相似,与无 CFS 的模型相比则更好。RETTS的AuROC(95% CI)从0.67(0.61-0.74)提高到0.83(0.79-0.88)(p = 0.008),NEWS的AuROC(95% CI)从0.53(0.45-0.61)提高到0.82(0.77-0.87)(p <0.001),TEWS的AuROC(95% CI)从0.63(0.55-0.71)提高到0.82(0.77-0.87)(p = 0.002)。 结论 与单独使用 RETTS 或早期预警评分相比,使用 CFS 结合 RETTS 或使用 NEWS 或 TEWS 进行结构化生命体征评估来衡量虚弱程度更能预测 30 天死亡率。更好的预后预测可提供更切合实际的预期,从而在急诊室流程的早期与患者进行知情讨论并启动个体化治疗计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Addition of the clinical frailty scale to triage tools and early warning scores improves mortality prognostication at 30 days: A prospective observational multicenter study

Objectives

Frailty, assessed with clinical frailty scale (CFS), alone or in combination with aggregated vital signs, has been proposed as a measure to better predict mortality of older patients in the emergency department (ED), but the added predictive value to conventional triage is unclear.

Methods

This was a secondary analysis of a prospective observational study in three EDs in Sweden that evaluated the prognostic performance of the CFS alone or in combination with the national early warning score (NEWS), triage early warning score (TEWS) or the rapid emergency triage and treatment system (RETTS) triage tool using logistic regression. The primary outcome was 30-day mortality with 7- and 90-day mortality and admission as secondary outcomes reported as area under the receiver operating curve (AuROC) scores with 95% confidence intervals (CIs). The sensitivity, specificity, accuracy, predictive values, and likelihood ratios are reported for all models.

Results

A total of 1832 patients were included with 17 (0.9%), 57 (3.1%), and 121 (6.6%) patients dying within 7, 30, and 90 days, respectively. The admission rate was 43% (795/1832). Frailty (CFS > 4) was significantly associated with 30-day mortality (odds ratio 6, 95% CI 3‒12, p < 0.01). Prognostication of 30-day mortality was similar for all CFS-based models and better compared with models without CFS. The AuROC (95% CI) improved for RETTS from 0.67 (0.61‒0.74) to 0.83 (0.79‒0.88) (p = 0.008), for NEWS from 0.53 (0.45‒0.61) to 0.82 (0.77‒0.87) (p < 0.001), and for TEWS from 0.63 (0.55‒0.71) to 0.82 (0.77‒0.87) (p = 0.002).

Conclusion

Frailty measured with the CFS in combination with RETTS or structured vital sign assessment using NEWS or TEWS was better at prognosticating 30-day mortality compared to RETTS or early warnings score alone. Improved prognostication provides more realistic expectations and allows for informed discussions with patients and initiation of individualized treatment plans early in the ED process.

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